Electrocardiography

Also known as ECG

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Overview

Electrocardiography analyzes electrical waveforms recorded from the heart to identify rhythm disorders, measure cardiac intervals, and screen for conditions such as heart failure or myocardial infarction. Common methods include signal processing and waveform delineation, supervised CNN and Transformer classifiers, and self-supervised foundation models; multimodal approaches also align ECGs with clinical text or signals such as PPG. Researchers evaluate these systems on benchmarks including PTB-XL and MIT-BIH, as well as clinical datasets such as MIMIC-IV-ECG, for tasks ranging from beat classification to long-term monitoring and ECG reconstruction. A central challenge is making strong benchmark results hold across hospitals, patient groups, devices, and recording conditions while providing explanations and evidence that clinicians can trust.

Latest papers

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108 papers11 papers in the last four weeks, down 31% on the four weeks before. 0.1% of all new papers.

  1. Foundation Model for Cardiac Time Series via Masked Latent Attention

    Mar 27, 2026Moritz Vandenhirtz, Samuel Ruipérez-Campillo, Simon Böhi +6Electrocardiogram Representation LearningElectrocardiogram Foundation Models

    Department of Computer Science, ETH Zurich, Switzerland · Department of Biomedical Engineering, University of Basel, Switzerland

  2. MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and management

    Mar 23, 2026Jack W O'Sullivan, Mohammad Asadi, Lennart Elbe +10Medical VLMsMultimodal Understanding

    Division of Cardiology, Department of Medicine, Stanford University, CA, USA · Department of Biomedical Data Science, Stanford University, CA, USA · Department of Electrical Engineering, Stanford University, CA, USA +7

  3. Shift-Invariant Feature Attribution in the Application of Wireless Electrocardiograms

    Mar 20, 2026Yalemzerf Getnet, Abiy Tasissa, Waltenegus DargieFeature AttributionElectrocardiography

    Department of Electrical and Computer Engineering at Addis Ababa University, Ethiopia · Department of Mathematics, Tufts University, USA · Faculty of Computer Science, Technische Universität Dresden, 01062 Dresden, Germany

  4. Holter-to-Sleep: AI-Enabled Repurposing of Single-Lead ECG for Sleep Phenotyping

    Mar 19, 2026Donglin Xie, Qingshuo Zhao, Jingyu Wang +9Wearable Health MonitoringElectrocardiography

    National Institute of Health Data Science, Peking University, Beijing, China · Institute of Medical Technology, Peking University Health Science Center, Beijing, China · Department of Computer Science, Tianjin University of Technology, Tianjin, China +6

  5. Stress Classification from ECG Signals Using Vision Transformer

    Mar 19, 2026Zeeshan Ahmad, Naimul KhanElectrocardiogram ClassificationElectrocardiography

  6. Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

    Mar 18, 2026Youssef Youssef, Jitin SinglaMulti-View Contrastive LearningElectrocardiography

    Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India · Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee 247667, India

  7. Vib2ECG: A Paired Chest-Lead SCG-ECG Dataset and Benchmark for ECG Reconstruction

    Mar 16, 2026Guorui Lu, Xiaohui Cai, Todor Stefanov +1ElectrocardiographyWearable Health Monitoring

    Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Leiden, The Netherlands. · the School of Computer Science and Technology, University of Science and Technology of China, Anhui, China.

  8. Complementarity-Preserving Generative Theory for Multimodal ECG Synthesis: A Quantum-Inspired Approach

    Mar 16, 2026Timothy Oladunni, Farouk Ganiyu-Adewumi, Clyde Baidoo +1Multimodal GenerationElectrocardiography

    Department of Computer Science, Morgan State University, Baltimore, MD, USA

  9. ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation

    Mar 15, 2026Jungwoo Oh, Hyunseung Chung, Junhee Lee +6Electrocardiogram InterpretationClinical Reasoning

    KAIST · Ajou University School of Medicine · Yonsei University College of Medicine +1

  10. ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model

    Mar 4, 2026Yuhao Xu, Xiaoda Wang, Yi Wu +3Electrocardiogram Foundation ModelsElectrocardiography

    Department of Computer Science, Emory University, Atlanta, GA 30307 · School of Computer Science, University of Oklahoma, Norman, OK 73019 · Center of Data Science, Emory University, Atlanta, GA 30307

  11. Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors

    Mar 3, 2026Ya Zhou, Zhaohong Sun, Tianxiang Hao +1Electrocardiogram ClassificationElectrocardiography

    Department of Information Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China · The Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China · National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, 100037, China

  12. A Novel end-to-end Digital Health System Using Deep Learning-based ECG Analysis

    Feb 28, 2026Artemis Kontou, Natalia Miroshnikova, Costakis Matheou +4ElectrocardiographyElectrocardiogram Classification

    KIOS Research and Innovation Center of Excellence (KIOS CoE), University of Cyprus, Panepistimiou 1, Aglantzia 2109, Cyprus · MEDTL Medical Technologies Ltd., 91 Limassol Avenue, Aglantzia, Office 202, Nicosia 2121, Cyprus · Department of Computer Science, University of Cyprus, Panepistimiou 1, Aglantzia 2109, Cyprus

  13. How Well Do Multimodal Models Reason on ECG Signals?

    Feb 27, 2026Maxwell A. Xu, Harish Haresamudram, Catherine W. Liu +11Electrocardiogram InterpretationMultimodal Model Evaluation

    University of Illinois Urbana Champaign · Google Inc · Rush University +4

  14. Learning geometry-dependent lead-field operators for forward ECG modeling

    Feb 25, 2026Arsenii Dokuchaev, Francesca Bonizzoni, Stefano Pagani +2ElectrocardiographyNeural Surrogate Modeling

    Laboratory of Mathematics for Biology and Medicine, Università di Trento, Italy · MOX Laboratory, Department of Mathematics, Politecnico di Milano, Italy · Euler Institute, Università della Svizzera italiana, Switzerland

  15. When Should a Model Change Its Mind? An Energy-Based Theory and Regularizer for Concept Drift in Electrocardiogram (ECG) Signals

    Feb 25, 2026Timothy Oladunni, Blessing Ojeme, Kyndal Maclin +1Concept DriftElectrocardiography

    Department of Computer Science, Morgan State University, Baltimore, MD, USA.

  16. CG-DMER: Hybrid Contrastive-Generative Framework for Disentangled Multimodal ECG Representation Learning

    Feb 24, 2026Ziwei Niu, Hao Sun, Shujun Bian +4Electrocardiogram Representation LearningMultimodal Disentangled Representation Learning

    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore · College of Computer Science and Technology, Zhejiang University, Hangzhou, China · College of information science and engineering, Ritsumeikan university, ibaraki Osaka, Japan +1

  17. ELF: A Family of Encoder-Free ECG-Language Models

    Jan 5, 2026William Han, Tony Chen, Chaojing Duan +6HealthcareElectrocardiography

    Carnegie Mellon University, USA · Allegheny Health Network, USA · University of California, Los Angeles, USA +1

  18. PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection

    Sep 24, 2025Xiaocheng Fang, Jiarui Jin, Haoyu Wang +8ElectrocardiographyConditional Generation

    National Institute of Health Data Science, Peking University, China · School of Intelligence Science and Technology, Peking University, China · University of Chinese Academy of Sciences, China +1